N. Dikshan
Papers
1
Total Citations
12
H-Index
1
About
N. Dikshan is a researcher in Natural Language Processing (NLP), with a focused expertise on Named Entity Recognition (NER) for Indian languages. Their most-cited work, a 2017 survey on various approaches used in NER for Indian languages, has garnered 12 citations and serves as a foundational resource for researchers tackling the unique challenges of multilingual and morphologically rich text. Dikshan’s contributions lie in systematically reviewing and comparing NER methodologies—from rule-based to machine learning and hybrid systems—highlighting their critical role in information extraction, automated text processing, and applications spanning artificial intelligence, robotics, and bioinformatics. By mapping the landscape of NER techniques for Indian languages, Dikshan has helped bridge a significant gap in NLP research, enabling more accurate and culturally relevant text analysis. Their work underscores the importance of NER as a key enabler for industries and academia alike, advancing the field’s capacity to process diverse linguistic data. Dikshan’s survey remains a valuable reference for students and researchers seeking to understand and improve NER systems in under-resourced language contexts.
Research Focus
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Top Papers
- 1